Generating Sensor-Based Identifier

1. A system for generating a sensor-based identifier of a client device, comprising: at least one computing device; and an application executed by the at least one computing device, wherein the application causes the at least one computing device to at least: obtain a first request to access a resource from a client device over a network; transmit a second request for a sensor-based identifier of the client device to the client device; obtain an audio sample from the at least one computing device from the client device, the audio sample generated by playback and recording of a high-frequency reference sample by the client device, the audio sample comprising the high-frequency reference sample and ambient noise, the audio sample further being unique to the client device and based upon a hardware variance of at least one speaker and at least one microphone of the client device relative to other client devices; generate the sensor-based identifier of the client device based upon the audio sample, the sensor-based identifier being unique to the client device and based upon the hardware variance of the at least one speaker and the at least one microphone of the client device relative to the other client devices, wherein the sensor-based identifier comprises an alphanumeric identifier generated based on an acoustic feature of the audio sample; authenticate the client device based upon the sensor-based identifier and a previously generated sensor-based identifier that is stored in a data store accessible to the at least one computing device, wherein authenticating the client device comprises generating a confidence score based on a comparison between alphanumeric identifier and the previously generated sensor-based identifier; and grant the client device access to the resource in an instance in which the confidence score meets a threshold.

2. The system of claim 1 , wherein the application generates the previously generated sensor-based identifier by at least: causing the client device to initiate the playback of the high-frequency reference sample through a speaker system; causing the client device to initiate capture of another audio sample using a microphone system of the client device; and wherein the previously generated sensor-based identifier is generated based upon the other audio sample.

3. The system of claim 2 , wherein the other audio sample is longer than the audio sample.

4. The system of claim 1 , wherein the high-frequency reference sample is ultrasonic.

5. The system of claim 1 , wherein the high-frequency reference sample is greater than about 18 kHz.

6. The system of claim 1 , wherein the at least one computing device generates the sensor-based identifier by: performing a noise suppression algorithm to remove the ambient noise from the audio sample; extracting at least one acoustic feature from the audio sample; and generating the sensor-based identifier by generating a fingerprint from the at least one acoustic feature.

7. The system of claim 1 , wherein the second request for the sensor-based identifier of the client device contains at least one of a reference to the high-frequency reference sample or a copy of the high-frequency reference sample, wherein the high-frequency reference sample is inaudible to a human being.

8. A method comprising: obtaining a first request to access a resource from a client device over a network; transmitting a second request for a sensor-based identifier of the client device to the client device; obtaining an audio sample from a computing device from the client device, the audio sample generated by playback and recording of a high-frequency reference sample by the client device, the audio sample comprising the high-frequency reference sample and ambient noise, the audio sample further being unique to the client device and based upon a hardware variance of at least one speaker and at least one microphone of the client device relative to other client devices; generating the sensor-based identifier of the client device based upon the audio sample, the sensor-based identifier being unique to the client device and based upon the hardware variance of the at least one speaker and the at least one microphone of the client device relative to the other client devices, wherein the sensor-based identifier comprises an alphanumeric identifier generated based on an acoustic feature of the audio sample; authenticating the client device based upon the sensor-based identifier and a previously generated sensor-based identifier that is stored in a data store accessible to the computing device, wherein authenticating the client device comprises generating a confidence score based on a comparison between the alphanumeric identifier and the previously generated sensor-based identifier; and granting the client device access to the resource in an instance in which the confidence score meets a threshold.

9. The method of claim 8 , wherein the previously generated sensor-based identifier is generated by at least: causing the client device to initiate the playback of the high-frequency reference sample through a speaker system; and causing the client device to initiate capture of another audio sample using a microphone system of the client device; wherein the previously generated sensor-based identifier is generated based upon the other audio sample.

10. The method of claim 9 , wherein the other audio sample is longer than the audio sample.

11. The method of claim 8 , wherein the high-frequency reference sample is ultrasonic.

12. The method of claim 8 , wherein the high-frequency reference sample is greater than about 18 kHz.

13. The method of claim 8 , wherein generating the sensor-based identifier further comprises: performing a noise suppression algorithm to remove the ambient noise from the audio sample; extracting at least one acoustic feature from the audio sample; and generating the sensor-based identifier by generating a fingerprint from the at least one acoustic feature.

14. The method of claim 8 , wherein the second request for the sensor-based identifier of the client device contains at least one of a reference to the high-frequency reference sample or a copy of the high-frequency reference sample, wherein the high-frequency reference sample is inaudible to a human being.

15. A non-transitory computer-readable medium embodying a program executable on at least one computing device, wherein the program, when executed, causes the at least one computing device to at least: obtain a first request to access a resource from a client device over a network; transmit a second request for a sensor-based identifier of the client device to the client device; obtain an audio sample from the at least one computing device from the client device, the audio sample generated by playback and recording of a high-frequency reference sample by the client device, the audio sample comprising the high-frequency reference sample and ambient noise, the audio sample further being unique to the client device and based upon a hardware variance of at least one speaker and at least one microphone of the client device relative to other client devices; generate the sensor-based identifier of the client device based upon the audio sample, the sensor-based identifier being unique to the client device and based upon the hardware variance of the at least one speaker and the at least one microphone of the client device relative to the other client devices, wherein the sensor-based identifier comprises an alphanumeric identifier generated based on an acoustic feature of the audio sample; authenticate the client device based upon the sensor-based identifier and a previously generated sensor-based identifier that is stored in a data store accessible to the at least one computing device, wherein authenticating the client device comprises generating a confidence score based on a comparison between the alphanumeric identifier and the previously generated sensor-based identifier; and grant the client device access to the resource in an instance in which the confidence score meets a threshold.

16. The non-transitory computer-readable medium of claim 15 , wherein the program causes creation of the previously generated sensor-based identifier by at least: causing the client device to initiate the playback of the high-frequency reference sample through a speaker system; and causing the client device to initiate capture of another audio sample using a microphone system of the client device; wherein the previously generated sensor-based identifier is generated based upon the other audio sample.

17. The non-transitory computer-readable medium of claim 15 , wherein the high-frequency reference sample is greater than about 18 kHz.

18. The non-transitory computer-readable medium of claim 15 , wherein the program generates the sensor-based identifier by: performing a noise suppression algorithm to remove the ambient noise from the audio sample; extracting at least one acoustic feature from the audio sample; and generating the sensor-based identifier by generating a fingerprint from the at least one acoustic feature.

19. The non-transitory computer-readable medium of claim 15 , wherein the second request for the sensor-based identifier of the client device contains at least one of a reference to the high-frequency reference sample or a copy of the high-frequency reference sample, wherein the high-frequency reference sample is inaudible to a human being.

20. The non-transitory computer-readable medium of claim 15 , wherein the second request comprises a command to the client device to provide the audio sample with a specified length and to include the high-frequency reference sample which is unique to the client device.